High-performance metabolic profiling with dual chromatography-Fourier-transform mass spectrometry (DC-FTMS) for study of the exposome

• Type of Material: Article
• Authors: Quinlyn A. Soltow, Emory University; Frederick Strobel, Emory University; Keith G. Mansfield, Harvard University; Lynn Wachtman, Harvard University; Youngja Park, Emory University; Dean P Jones, Emory University
• Language: English
• Date: 2013-03-01
• Publisher: Springer Verlag (Germany)
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2011 Springer Science+Business Media, LLC.
• Final Published Version (URL): http://dx.doi.org/10.1007/s11306-011-0332-1
• Title of Journal or Parent Work: Metabolomics
• ISSN: 1573-3882
• Volume: 9
• Issue: 1
• Start Page: S132
• End Page: S143
• Grant/Funding Information: This work was supported by research NIH grants P01ES016731 (DPJ); R01AG038746 (DPJ); R01ES011195 (DPJ); and P51RR000168 (KGM).
• Keywords: Metabolomics; EXPOSURE; HEALTH; Anion exchange; Life Sciences & Biomedicine; PLATFORM; Science & Technology; FT-ICR; LC/MS; Endocrinology & Metabolism; Predictive health; POLLUTANTS; Reverse phase; Exposome; Plasma; HUMAN PLASMA; Personalized medicine; STRATEGY
• Research Categories: Health Sciences, Medicine and Surgery

Abstract

Studies of gene-environment (G × E) interactions require effective characterization of all environmental exposures from conception to death, termed the exposome. The exposome includes environmental exposures that impact health. Improved metabolic profiling methods are needed to characterize these exposures for use in personalized medicine. In the present study, we compared the analytic capability of dual chromatography-Fourier-transform mass spectrometry (DC-FTMS) to previously used liquid chromatography-FTMS (LC-FTMS) analysis for high-throughput, top-down metabolic profiling. For DC-FTMS, we combined data from sequential LC-FTMS analyses using reverse phase (C18) chromatography and anion exchange (AE) chromatography. Each analysis was performed with electrospray ionization in the positive ion mode and detection from m/z 85 to 850. Run time for each column was 10 min with gradient elution; 10 μl extracts of plasma from humans and common marmosets were used for analysis. In comparison to analysis with the AE column alone, addition of the second LC-FTMS analysis with the C18 column increased m/z feature detection by 23-36%, yielding a total number of features up to 7,000 for individual samples. Approximately 50% of the m/z matched to known chemicals in metabolomic databases, and 23% of the m/z were common to analyses on both columns. Database matches included insecticides, herbicides, flame retardants, and plasticizers. Modularity clustering algorithms applied to MS-data showed the ability to detection clusters and ion interactions. DC-FTMS thus provides improved capability for high-performance metabolic profiling of the exposome and development of personalized medicine.